# Mamba: Linear-Time Sequence Modeling with Selective State Spaces

> Gu and Dao's ICLR 2024 paper makes SSM parameters input-dependent, enabling content-aware sequence modeling at O(L) complexity. Mamba-1.4B matches Pythia-6.9B on language modeling perplexity while delivering 5x higher inference throughput than Transformers at sequence length 2K.

Canonical URL: https://kravhal.kcsatish.com/insights/week-08
Edition: Week 04 · March 2026
Tags: Deep Learning, Efficiency, Optimization
Reading time: 15 min read

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